Final Program - Society for Risk Analysis

P.90 Clarke CE; cec54@cornell.eduCornell UniversityINVESTIGATING THE ROLE OF IDENTITIES AND OPINION LEAD-ERSHIP ON RISK INFORMATION SEEKING AND SHARING ABOUTPROPOSED NATURAL GAS DRILLING IN NEW YORK’S MARCELLUSSHALEPotential development of Marcellus Shale natural gas reserves in New YorkState has spurred passionate debate and provided opportunities for gathering andexchanging information about perceived impacts. This project investigates the rolethat identities, specifically opinion leadership, play in motivating risk informationseeking and sharing about such risk controversies. Thirty-six interviews explore thenovel premise that an opinion leader identity and the contexts in which it emerges(including group membership and social roles) helps people negotiate a complex riskmessage environment and shapes communication behavior over time. Intervieweesperceived and sought and exchanged information about a variety of potential impactsand reported a variety of meanings associated with opinion leadership (including stayinginformed about particular impacts) and reasons for seeing themselves/being seenin this light (i.e., belonging to organizations such as local Legislatures and occupyingparticular positions, such as an elected official). For some, these contexts shaped thetypes of information about which they felt social or personal pressure to remaininformed and/or sought and shared. Theoretical and practical implications of thisresearch are discussed, including (1) measuring how people look for and exchange informationabout controversial, polarizing risk issues and (2) harnessing the power ofopinion leaders - themselves a diverse group - to encourage communication behaviorabout contentious natural resource management issues as part of public participatoryprocesses.P.124 Clewell HJ, Efremenko A, Black M, Thomas RS, McKim J, Wilga PC,Arnold LL, Gentry PR, Yager JW; hclewell@thehamner.orgThe Hamner Institutes for Health Sciences, CeeTox, Inc., University of Nebraska Medical Center,Environ International, University of New Mexico, AlbuquerqueGENOMIC CHANGES IN PRIMARY HUMAN UROEPITHELIALCELLS FOLLOWING 24 HOUR EXPOSURE TO MIXTURES OF ARSE-NITE AND ITS TRIVALENT METHYLATED METABOLITESExpression changes in arsenic-exposed primary human uroepithelial cells wereevaluated to identify genomic biomarkers of cell signal pathway perturbations potentiallyassociated with bladder carcinogenicity. Human uroepithelial cells from 10kidney-donor ureter segments were treated in culture with mixtures of inorganic arsenicand its trivalent metabolites for 24 hours at relative proportions (1:1:4) typicallyobserved in the urine of individuals exposed to arsenic in drinking water. Totalarsenic concentrations ranged from 0.06 to 18 micromolar. Similar responses were78obtained for mixtures containing pentavalent or trivalent metabolites. Principal componentanalysis indicated that the variation across individuals was substantially greaterthan the changes in expression elicited by arsenic treatment. However, a suite of genechanges was identified that reflects the effects of sub-micromolar arsenic on a numberof key signaling pathways across nearly all subjects: HMOX1 (oxidative stress),FKBP5 (protein folding), LGALS8 (growth regulation), MT1E (metallothionine regulation),DDB2 (DNA damage sensing), TXN/TXNRD1 (thioredoxin regulation)and THBD (immune response). The concentration/response for DDB2 and THBDwere non-monotonic, with reversal in direction of effect around 0.1 micromolar. Together,these genes may serve as an early biomarker of effects for arsenic. Work isunderway to investigate changes in gene expression over time.M2-I.1 Cole D, Hoekstra M; dcole@cdc.govCenters for Disease Control and PreventionUSE OF CONSUMPTION DATA TO INFORM HUMAN ILLNESS SUR-VEILLANCE DATARegulatory decision-making needs to be informed by probability-based risksof foodborne disease at the food source or commodity level. However, food sourceattribution estimates rely heavily on human illness surveillance data collected by publichealth agencies, and the majority of these data lack food exposure information.Consequently, models of food source attribution need to incorporate consumptioninformation into estimates of population-based risk of foodborne illness outcomes.Consumption-based models can approach the issue using various underlying assumptionsand outputs. For example, a foundation for considering population-level attributionis to start with an assumption that all food is contaminated uniformly. Inthis case, the illness attribution fractions for each commodity are simple functionsof consumption estimates for each commodity. From this naïve hypothesis avariety of data sources can be incorporated to better reflect the true variation of contaminationacross food commodities. An example of this is the use of microbial datafrom commodity sampling to inform estimates of foodborne illness derived fromconsumption. These and other options for using consumption-based approaches toestimate food source attribution and to inform decisions based on these estimates willbe presented.T4-I.4 Coles JB, Zhuang J; johnbcoles@gmail.comState University at BuffaloPARTNERSHIP OPTIMIZATION DECISION SUPPORT SYSTEM(PODSS): IMPROVING PARTNERSHIP DEVELOPMENT AND RE-SOURCE ALLOCATION IN DISASTER RECOVERY OPERATIONS US-ING GAME THEORYThe Partnerships Optimization Decision Support System (PODSS) approachprovides a dynamic planning and coordination tool for surviving agencies to allocate